Abstract
Purpose of the Review
One of the major threats to tree health, and hence the resilience of forests and their provision of ecosystem services, is new and emerging pests. Therefore, forest health monitoring is of major importance to detect invasive, emerging and native pest outbreaks. This is usually done by foresters and forest health experts, but can also be complemented by citizen scientists. Here, we review the use of citizen science for detection and monitoring, as well as for hypothesis-driven research and evaluation of control measures as part of forest pest surveillance and research. We then examine its limitations and opportunities and make recommendations on the use of citizen science for forest pest monitoring.
Recent Findings
The main opportunities of citizen scientists for forest health are early warning, early detection of new pests, monitoring of impact of outbreaks and scientific research. Each domain has its own limitations, opportunities and recommendations to follow, as well as their own public engagement strategies. The development of new technologies provides many opportunities to involve citizen scientists in forest pest monitoring. To enhance the benefits of citizen scientists’ inclusion in monitoring, it is important that they are involved in the cocreation of activities.
Summary
Future monitoring and research may benefit from tailor-made citizen science projects to facilitate successful monitoring by citizen scientists and expand their practice to countries where the forest health sector is less developed. In this sense, citizen scientists can help understand and detect outbreaks of new pests and avoid problems in the future.
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Introduction
Forests are complex ecosystems that provide many ecosystem services, but are under pressure for several reasons like climate change or emerging and invasive alien pests [1,2,3,4]. Climate change has increased the risks to forest health, as trees weaken as a result of drought, windthrow, or other large-scale climatic events [5]. Impacts from pests and diseases are also increasing: there new arrivals of potential invasive alien pest species [6], and increasing outbreaks of native species (‘emerging and irruptive pests’). Combined with these threats, humans are increasingly cutting forests unsustainably or accommodating potential invasive pests and irruptive species into forests [7]. It is important to increase monitoring, protective measures and actions related to forest health, including the detection of pest outbreaks and invasive pests, in order to avoid ecological and economic damage [8].
Forest health can be defined as an integration of utilitarian and ecosystem measures of forest conditions and functions, applied to a range of spatial scales [9]. This means that even a healthy forest is expected to have tree mortality due to biotic and abiotic factors (i.e. including ‘pests’ and diseases) and to exhibit resilience around a dynamic equilibrium of the forest structure and function [9, 10]. When its status exceeds this natural expectation, this can be regarded as an ‘unhealthy’ forest. There are many drivers of forest health, including forest pests and diseases (Fig. 1; [11]). Pests and diseases can be a response of other drivers, e.g. climate change, and so can be an indicator of the impacts of that driver, or they can be a direct driver of change in the forests themselves [12].
In the current paper, we focus on forest insect pests and diseases. These can be among the most destructive causes of changes in tree and forest health. For instance, the European spruce bark beetle in Central Europe [13] or the Emerald ash borer in North America and Russia [14] have each killed millions of trees. Forest pests include invasive alien species (i.e. new introductions to a region) and emerging and native irruptive pests [8]. In order to address the issue of forest pests, an integrated approach of forest pest management is needed, requiring early detection, monitoring populations and assessing the impact of interventions, all informed by species research. This approach primarily entails eradication, i.e. early warning and early detection of population changes, followed by containment and management of outbreaks [8]. To achieve this, monitoring data from forests is required to support timely action, where this is possible, and to gain a better understanding of forest health.
Monitoring of and research on forest pests is typically done by foresters or forest health experts [15]. However, citizen science is a valuable tool for monitoring and research; it has demonstrated potential to support monitoring of and research on forest pests, and it has the additional benefit of engaging the public in forest health [16].
Citizen science is defined as the voluntary involvement of people in scientific research and monitoring [17]; their involvement usually includes collection of data, but can also include question formulation at project inception, co-design of methodologies, data analysis and disseminating results. Citizen science is diverse, covering approaches from structured surveys to opportunistic recording, approaches with specialist volunteer audiences to mass participation and simple to elaborate approaches [18]. Despite the diversity of approaches, they all share the outcome of providing data that is valuable for scientific research and monitoring. This means that citizen science requires a clear purpose and the use of appropriate tools and methodologies [19]. Citizen science should be evaluated against its ability to provide data that are fit for their intended purpose [20].
Citizen science can engage a wide range of different people, so should not be restricted to recruiting the ‘general public’. For instance, citizen science can involve the voluntary participation of any public audience, including small woodland owners and recreational users of forests. Experts and researchers may, of course, also be included in the monitoring as volunteers. Understanding the motivations of those involved is important. Recording wildlife through citizen science has a long history, especially in northwestern Europe (e.g. [21]). Often, citizen science is regarded as an intentional leisure activity, and recent studies have suggested that it particularly appeals to those who are relatively affluent and well-educated [22, 23]. This can be valuable when the focus is on the data that are collected, but specific types of citizen science can appeal more widely.
Both citizen science and work by professionals (i.e. forest managers and forest health professionals who are employed or contracted by relevant organisations concerned with forestry) can support monitoring and research on forest health (Fig. 1). Therefore, when considering forest pests and diseases, it is important to evaluate how and when citizen science can support, complement or augment the existing work undertaken by professionals.
The aim of this paper is to show the development and vision of citizen science in pest monitoring in forests. In the last decade, there has been an increased interest in citizen science and its potential in forest pest monitoring, especially in early detection of invasive pests. We have taken an integrated view of forest pest monitoring, where we not only focused on early detection, but we also took into account less investigated purposes such as early warning or monitoring of emerging and native pests, or their impacts. We will show the limitations and opportunities for citizen science and prepare recommendations for future projects for monitoring.
Part 1: Opportunities for Citizen Science: Reflecting on Past Projects
Citizen science can be used in different ways to monitor forest pests, both irruptive pests and emerging and new pests, and has implications for forest management ([18]; Fig. 2, Table 1). For both irruptive pests and emerging and new pests, citizen science can be used for early warning, impacts, long-term monitoring and science (Fig. 2). However, in these cases, the motivation of the participants, the tools used and the forest management activities vary. For example, in early warning of outbreaks of irruptive pests, citizen science data can be used to prepare risk maps, while for emerging and new pests, citizen science information on pests outbreaks from other countries on native trees with similar climatic situations can be used for the preparation of alert lists of potential new or emerging pests. Monitoring population dynamics is a citizen science activity typical for irruptive pests, while early detection and monitoring of spread are more pertinent for emerging and new pests. Below, we discuss how citizen science can be embedded in three activities: early detection and early warning of new pests, early detection of outbreaks and impacts and biological research.
Early Warning and Early Detection of Invasive Pest Species
Box 1 Different types of citizen science projects that can be used for insect pest monitoring.
Opportunistic (or passive, or unstructured) citizen science: Opportunistic citizen science projects are those in which biodiversity data are collected from volunteers when and where they choose, without data being captured according to specific recording protocols. Data on forest pests can be extracted from across the world, but because the records are usually presence-only based, they must be interpreted with caution. There are several platforms available to submit these records such as iNaturalist (www.inaturalist.org) and Observation.org (world.observation.org). The data can be used for surveillance of invasive and emerging pests Structured citizen science: Volunteers follow scientifically designed protocols at set times and/or places. By controlling the data collection process, the data are more useful for systematic monitoring, but this requires a higher level of commitment from volunteers, advance planning by scientists and long-term commitment from funders. These projects can be used for monitoring and hypothesis-driven research |
Targeted species recording: Projects that aim to survey or monitor a particular species or species group in a certain area. For instance, LIFE ARTEMIS (www.invazivke.si; [36••]) is a citizen science project focused on the early detection of alien pests in the forests of Slovenia. In this project, a mobile app and a website were developed for recording the alien species and data were confirmed by experts. Whenever notable records were received, this was quickly communicated to the national authorities Bioblitz: A short period of surveying living organisms in a designated area [37]. The bioblitz gives a snapshot overview of the biodiversity in a short time, which can inform on-the-ground management and decision-making organisations on the presence of species and in the case of forest pest monitoring, new and emerging pests |
Early warning and early detection of new and emerging pests are required to identify potential pests as soon as they move out of their natural range and to identify pathways of introduction and high-risk areas [38, 39••]. When an invasive pest species is detected for the first time, it has to be managed (and potentially eradicated) as soon as possible to avoid spread and potential impact on the ecosystem, economy and human health, and to assess their potential risks and ascertain potential management measures. Many plant health professionals are working in the field of early detection or risk management, and there are many examples of the success of early detection and consequent rapid response. One of the main highlights is the Asian longhorn beetle (Anoplophora glabripennis), which according to EPPO [40] has been found in many European countries but so far has always been successfully eradicated in Europe. However, there are also some examples where the species was not detected (or managed) early enough for successful eradication, like for Citrus longhorn beetle (Anoplophora chinensis) and Japanese beetle (Popillia japonica) in Italy [41, 42], the emerald ash borer (Agrilus planipennis) in Russia [43] or Oak Processionary moth (Thaumetopoea processionea) in the UK [44]. Citizen scientists can support early warning or early detection of species in forest and non-forest areas where there are trees (e.g. parks and gardens).
Early warning is the advance notice of species that could become a risk. Although early warning is an essential element of monitoring plant health using citizen science, this aspect is often under-promoted in scientific publications which deal with the surveillance of forest pests. In fact, volunteers who identify potentially invasive species can form an important early warning network for tree health [45, 46]. By regularly screening (social) media, scientific publications and citizen science databases like iNaturalist, new, emerging or recurring pests can be identified [25, 47••]. This information helps risk assessors and risk managers to prepare for and prevent possible outbreaks of new plant pests and diseases. By using this horizon scanning, the European Food Safety Authority (EFSA) and the European and Mediterranean Plant Protection Organisation (EPPO) identify pests and pathogens that might be of concern to the European territory [48, 49]. Citizen science can come into play here via passive observations, because plant health authorities often search large citizen science platforms for potential new pest species. On the basis of these data, plant health organisations like EPPO, for example, prepare an Alert List to draw the attention of its member countries to certain pests that may pose a risk to them and to provide early warning [24]. Species highlighted during this process should be assessed, and pathways of introduction should be identified. From the pathways and biology of the species, risk maps can be developed. Although there are many potentials for citizen science in early warning, there are not (yet) many projects which are practising early warning or horizon scanning (e.g. the monitoring and management of Cerambyx cerdo in the Mediterranean region [50]), so this provides a good opportunity for citizen science to grow in this area.
On the basis of the early warning, early detection can be organised more efficiently and be more focused. Unlike in early warning, citizen science has already been widely applied in the early detection of invasive alien pests and diseases [26, 27•, 32, 36••, 51,52,53,54, 55••, 56, 57] and is suggested as a low-cost method of surveillance [26, 55••]. For instance, Kline et al. [53] report that a citizen science initiative was set up in Curry Country (Oregon) for the early warning and detection of sudden oak death caused by Phytophthora ramorum. Similarly, Barker et al. [54] state that another citizen science initiative called the Forest Health Ambassador Program was established in Oakville (Ontario, Canada) for the early detection of invasive pests from the urban forest. Seidel et al. [58] state that drawing records of specific forest pest species of interest from existing citizen science databases and platforms would help to provide a better overview of the distributions of these taxa [58]. The awareness raised by citizen science tools, such as taxonomic interest forums, recording platforms (e.g. iNaturalist) and social media platforms, may, in the future, even help to act as an early warning system for these pests [58].
It is important to react as soon as possible after successful early detection of forest pest species (whether native or alien); otherwise, an outbreak can become uncontrollable. However, there are many people who visit forests and can report the start of an outbreak. For instance, Brown et al. [47••] reported that in the Observatree project, a network of tree health volunteers was created. They were trained to recognise the symptoms of attacked trees and to report them and were well supported with feedback to maintain their motivation and participation. Arboreta are often visited by the general public, and so there are many possibilities for citizen science related to early warning in these places, such as the International Plant Sentinel Network [59], which is using a network of arboreta and botanical gardens to identify pests on non-native tree species. Another opportunity is the use of novel methods, like eDNA, remote sensing and the introduction of sentinel trees, i.e. trees that are specifically monitored for their health and the presence of pests and diseases [36••, 60]. These methods can be used by citizen science under guidance of forest health experts, and therefore, a larger area can be covered, and more samples can be taken for the detection of invasive pests. The use of citizen science in the early warning and early detection of invasive pests offers many opportunities for citizen science to work in collaboration with professional plant health specialists.
In the past, not all invasive pests were found in time or were not prioritised, which negatively affected the eradication outcome [55••, 61]. To avoid this in the future, the availability of a centralised system where observations are collected by a competent authority is important so that rapid response actions can be taken immediately [36••, 39••]. To encourage early detection of invasive forest pests, awareness-raising campaigns and the development of submission apps should be stepped up. More attention also needs to be paid to areas from which few observations are made.
Early Detection of Outbreaks (of Invasive or Native Species) and the Impacts of Pests
Monitoring pests and their impact is an important part of overall forest monitoring, and in many countries, it is undertaken by the forest management organisations. As with invasive species, it is important to detect outbreaks of native pests as soon as possible so that the requirement for action can be assessed. This means that there is value in many people on the ground surveying for potential outbreaks, which provides a clear role for citizen science. There are several citizen science projects in which people are surveying populations of irruptive and emerging pest species [28, 29•, 34••, 35••, 62]. For instance, Valdés-Correcher et al. [35••] focused on defoliator damage on oaks in order to investigate the interactions with other organisms. Similarly, Meentemeyer et al. [28] investigated the potential of citizen science to predict outbreaks of sudden oak death.
Surprisingly, less has been done on monitoring of abundance over time through citizen science. For this, relative or standardised measures of abundance or impact are valuable. Carleton and colleagues [29•] provided citizen scientists with pheromone traps to monitor the spruce budworm, which generated valuable spatio-temporal data for this species, and from which management implications could be inferred. Pocock and Evans [33] asked members of the public to record the degree of damage to horse chestnut (Aesculus hippocastanum) caused by the leaf-mining moth Cameraria ohridella. Another project focusing on schools and ecological networks in oak trees from all over Europe asked school children to send back leaves on which the infestation rate of defoliators (leaf chewers, miners and gallers) was assessed [35••]. If continued, this would be a good and simple method to monitor defoliators. In the Netherlands, the project ‘Natuurkalender’ is collecting data on the phenology of different groups of pest organisms. One of them is the emerging pest of the oak processionary moth (Thaumetopoea processionea), which has shown a strong spread in the recent years in the northwestern part of Europe.
Citizen science is often thought of as being most beneficial for getting lots of data from wide spatial extents via unstructured surveys (i.e. in which people collect data when and where they choose). Most previous projects only requested that citizen scientists record presence data on invasive alien species [27•, 36••, 63]. As a result, it is hard to distinguish places where the species is absent as there are locations where there are no observers. Although this could be statistically addressed in some cases, as de Groot et al. did for Oak lace bug (Corythuca arcuata) [64], an alternative approach is to standardise the monitoring. For example, ‘Observatree’ started a project on sentinel trees, in which volunteers adopt a tree and monitor it for potential invasive alien species and therefore also take into account the absence points [36••]. However, it can also be effective in providing data regularly over time, e.g. when the same sites are systematically surveyed over time (e.g. [65]). There is good potential for citizen science to deliver this type of data, which could provide high-quality data supporting the monitoring of pest outbreaks.
Monitoring the impacts of the pest is mostly focused on the health of the trees, and pests can be classified by their impact. Pests that cause low impact are those where no damage is observed and no intervention or management is required; medium-impact pest species cause damage and should be managed and controlled, but only in the short term, while high-impact species require management and control because they may have significant economic and environment effects [56]. Hence, in order to know the threat faced by forests, it is important to evaluate the state of the trees, and this is a valuable role for citizen science studies [28, 30, 32, 66••, 67]. One common practice is to register the symptoms of pest damage [30, 66••], or to develop a rigorous scoring system or index to record the health of the trees, e.g. stem and crown condition, allowing tree health evaluation to be comparable across space and time [52, 68, 69].
In addition, it is important to evaluate the impact on the biodiversity of the forest, but this is rarely considered in citizen science projects. Two citizen science studies [31, 70] demonstrated that the emerald ash borer, Agrilus planipennis, altered the community of insectivorous birds in the USA. Similarly, Valdés-Correcher et al. [35••] found that the herbivorous leaf gallers and leaf miners in oak trees (Quercus robur) were influenced by climatic factors and by leaf traits. These show the benefit of considering different aspects of the ecosystem, not just the insect forest pest or the tree health. They also demonstrate the value of sampling more variables at the same location to effectively understand the impacts of forest pests. Citizen science can also be used to identify host resistance to forest pests [71].
There are more opportunities in terms of tools and methods that may be useful for forest pest monitoring. In recent years, for example, drones have become very popular as a hobby, and this tool could also be used by citizen scientists to monitor, for instance, the pine processionary moth [72]. On the other hand, we can also learn a lot from other fields of study. Biodiversity conservation relies heavily on citizen science, and this involves monitoring the trends of butterflies, birds and other taxonomic groups in several countries [73, 74]. Methods such as transects, light traps or malaise traps applied in other projects [74,75,76,77] can also be used to monitor plant health to gain insight into the population dynamics of certain pest species. Organising dispersed bioblitzes (Box 1) is another innovative way of obtaining targeted biodiversity data in a certain area [37, 78]. It is also valuable to remember that citizen science projects can be used to record attributes of species, such as relative abundance or indices of impact, rather than simply presence [79].
Research of Species Biology with CS
Many aspects of the biology of pest species and their impacts require professional engagement. However, when working on a large-scale, systematic and or lab-based projects, there are many opportunities for citizen science to contribute knowledge about these species and their interactions. Studying the biology of forest pests by citizen scientists is rather uncommon. However, such participatory, hypothesis-driven research allows researchers to address questions about the pest biology of a species at larger spatial scales and with greater temporal resolution than would otherwise be feasible [33, 80]. A robust example is the ‘Conker Tree Science’ project where the parasitism of the horse-chestnut leaf miner, C. ohridella, by naturally occurring parasitoid wasps was successfully studied by citizen science participants [33]. They found that both leaf damage of horse chestnut and parasitoid attack on leaf-mining moths were greatest where the leaf-mining month had been present the longest. Also, plant-herbivore-natural enemy interactions were studied by both citizen scientists and schoolchildren. In this way, the latitudinal and climatic effects on the relationships between insect herbivory, leaf chemistry and bird attack rates were studied across the European geographic range of the pedunculate oak (Q. robur) [35••]. They found that climatic factors explained the variation of gall makers and leaf miners, and not the variation of leaf damage, leaf defences and bird attack rates, and that leaf traits influenced both gall makers and leaf miners, whereas both leaf traits and bird attack rates did not vary with leaf damage. These results improve the understanding of the mechanisms driving geographical variation in the relationships between plant, herbivore and predators. In the Netherlands, the phenology project ‘de Natuurkalender’ (www.naturetoday.com) gives the phenology of the oak processionary moth over several years and provides the opportunity to investigate the influence of climate change on this species and its interactions with the phenology of its host.
An interesting opportunity is the use of sentinel trees by citizen science. Besides early warning of pests and diseases, other research questions can be investigated, such as increasing the understanding of known pests, identifying new pest-host associations, identifying potential biocontrol agents and supporting integrated management [59]. Another important underused part of citizen science is the study of species interactions [35••, 81]. These few examples show that studying the pest biology of forest health and their relationships with other species can be either the main or a secondary goal of citizen science projects.
Citizen science can also be a cost-effective way of gathering specimens from across a wide geographic range, with further biological analysis undertaken by professionals. In this way, new hosts for Phytophthera ramorum were identified from samples obtained during the Sudden Oak Death Blitz in California [82].
Engaging People with Forest Health and Management
Informing and raising public awareness about forest health and forest pest insects is very important to promote sustainable forest management and use. In many cases, citizen science is used for data collection, but public engagement about forest health is a really valuable impact for citizen science on forest pests because of the role the public can play in surveillance, monitoring and research, but also because their actions can directly affect these drivers of change, e.g. the introduction and spread of invasive species.
Recently, several surveys have revealed that public knowledge of tree pests and diseases and the measures to control them are generally low, although it varies among stakeholder groups [83,84,85,86]. These surveys also point out that the level of concern and acceptance of management actions tends to be high when individuals are aware of the problem [83, 84], although there are preferences for different types of action. For instance, mechanical removal was preferred in a survey conducted in Slovenian forests [86] and biological control in a UK survey [84], and there is an overall lack of support for chemical control [84, 86, 87]. Support for management is high when species are invasive [86, 88], but this may not be the case when the pest or disease is native [89]. Increasing public knowledge about the impact and biology of native and invasive pests is essential in order to gain public acceptance of the most appropriate management measures for each pest.
Given the high importance of public dialogue and understanding about forest health, several citizen projects have emphasised volunteer education and provided educational materials and training to support ongoing learning [53, 90, 91]. Participating in a citizen science project increases people’s awareness, understanding and engagement around environmental issues such as forest health [30, 91,92,93]. Volunteer training also has a ‘multiplier effect’, as concerned participants in citizen science can become ‘science communicators’ and a ‘supplementary source of communication to the public’ [55••]. For example, in a volunteer programme for early detection of new invasive species by private landowners in Minnesota, the volunteers who took part in a learning module were more likely to recruit volunteers than those who only received an invitation letter [46].
Forest health professionals can also respond to public concerns, for example in Western Australia, the community was concerned about a forest disease, and the impetus to create a citizen project (‘The Marri Canker project’) came from the local landowners observing the decline in local Marri populations [32]. Public dialogue and cocreation of projects are important in these cases of existing public concern to create effective citizen science [72].
Limitations in Citizen Science
In the previous sections, we have showed that there are many opportunities for citizen science in forest health. However, there are also limitations with citizen science, particularly when used as a tool for monitoring and research. The important limitations we have identified for citizen science data are limitations with species identification, concerns about data quality, uneven coverage of records in space and time and overall lack of fit-for-purpose of the dataset for its intended use.
The ability to correctly identify a species is a basic requirement for data on forest pests. Sometimes, actions need to be taken for particular species like the EU Quarantine species or alien pests that occur near the border of a country [36••], so accurate identification guides (e.g. [94]) to support correct identifications are important. Potential invasive or emerging pests may not be well known or sometimes not even known by science [95]. In the case of difficult taxa, it may be only very experienced people (professionals or expert amateurs) who can identify the species; sometimes, that may only be possible with molecular methods (and this may be especially so for disease-causing organisms, rather than pest invertebrates). There is also a bias in the traits that make species reportable or noticeable, with larger, more brightly coloured and strikingly patterned species being most likely to be reported [96]. To highlight pest species of concern, awareness-raising campaigns and identification guides are needed [36••]. Where possible, citizen science records can have confirmatory evidence (typically photographs, but could include sound recordings or specimens where appropriate) to allow species identification to be confirmed. Verifying records does require an investment in resources by the project organisers, although this task could also be carried out by trained volunteers [36••].
Species identification is only one component of data quality. Some critics express concern that citizen science data are of low quality [97], but there is a range of ways of ensuring data from citizen science are of good quality [98,99,100]. Different types of citizen science data can be collected, e.g. presence, abundance or attributes such as size [79]. These may vary in their precision and accuracy and, of course, also depend upon the skills and experience of the focal audience. An important aim is to ensure the quality of data acquired [33] and, if necessary, find ways to improve training, the quality of resources, or alter the methodology or even the aims of the study to ensure that quality is sufficient for the project’s purpose. For example, Castagneyrol et al. [34••] found that schoolchildren over-estimated the attack rate of artificial caterpillars through the citizen science project ‘Tree Bodyguards’. It was suggested that face-to-face courses would increase the quality of the data, or that scientists could reassess the data of the schoolchildren. Alternatively, Pocock et al. [33] considered data quality in a project on horse-chestnut leaf miner (C. ohridella). They used a simple, five-category method to facilitate accurate scoring of leaf damage, and from validated subsets of the data, they were able to statistically account for over-estimates of parasitoid numbers. The key requirement for citizen science is that the data are sufficiently accurate to be useful in the original project, although it is worth noting that many citizen science data can be reused in projects beyond the original one.
The limitation of uneven coverage of data is one that is often described, but in many cases, it is inevitable. Sometimes, this can be overcome with a highly structured design, but the restrictions of such projects typically lead to lower participation by volunteers. Citizen science then often focuses on the collection of unstructured data [26, 27•, 36••, 51,52,53,54, 55••, 56, 57] (Box 1), and these are typically biased towards areas with higher introduction risks (i.e. urban areas) [101,102,103,104,105]; thus, the biases can sometimes actually enhance the ability of citizen science to provide early detection. It is possible to statistically take account of these biases, although ideally, this should be planned at the inception of the study. Knowledge of these biases can support the provision of advice for where to search for pest species [64]. In theory, biases could arise intentionally driven by people’s concern about the use of the data if they deem forest management to be unacceptable [106••]. This should be highlighted through consultation at project inception and addressed through engagement and co-design.
Bias can also occur over time. Although citizen science is increasing, we should be concerned about the sustainability of people’s participation and also the risk of confusion in a plethora of projects. In order to improve the evaluation of the risk of alien forest pests to forest health, it is important to continuously monitor their impact on tree health over long periods of time. To this end, long-term projects [28] with an intensive monitoring network are required, as has already been proposed in early detection programmes [47••]. In California, for instance, the citizen science programme ‘Sudden Oak Death Blitz’ was carried out for 6 years [28]. To ensure that participants continue to participate over time, the evaluation of the impact on tree health may need to be simple, have complete and detailed guidelines [80], include intensive training and frequent interaction with the participants [54, 107, 108••], and may focus on the use of tools that facilitate data collection by participants, such as smartphone apps [66••, 107].
Thus far, we have considered the limitations of citizen science alone, but as part of an overall monitoring or research project, the relationship of citizen science to professional monitoring and research will need to be explored (Fig. 2). It is conceivable that forest health organisations could, in the future and for some specific purposes, rely almost entirely on citizen science (as is the case for national bird monitoring in countries like the UK). However, when considering the opportunties and limitations of citizen science (Table 1), professional monitoring will remain foundational for forest health organisations, but we expect that citizen science will have an increasingly valuable role in augmenting or complementing data from professionals to expand our current knowledge on forest pests.
Data flow can be an obstacle for some citizen science if the data are not shared efficiently. The data flow between citizen science projects and the professional organisation depends partly on whether or not the professional organisation organises the project. For instance, Observatree and LIFE ARTEMIS have developed projects for the early detection of forest pests and invasive alien species in the UK and Slovenia, respectively, with direct data flows to the national plant protection organisations [36••]. It is more difficult when the citizen science project is developed independently from the professional organisations like the citizen science platform iNaturalist, but Adriaens et al. [109] developed a pipeline to ensure data flow from GBIF on invasive alien species. However, this will be more of a limitation when citizen science platforms or projects are not freely accessible.
Overall, these concerns are about the fit-for-purpose of the citizen science data [20]. It is clear that the concerns of species identification, data quality and uneven coverage can (often) be addressed, but this should be done early in a project lifecycle and ideally through co-design or a testing phase prior to the project launch. This is part of the way of doing good citizen science as we go on to discuss in the following section.
Part 2: Where Do We Go from Here?
Ways of Doing Good Citizen Science
Before undertaking citizen science, it is important to critically consider the role and use of citizen science: citizen science will not always be the ideal approach to achieve the aims of a project organiser, whether those aims are for monitoring, for engagement or for both [85]. When citizen science is used, it needs to be designed to address the questions of interest [20, 110]. A formal cost–benefit evaluation of citizen science versus alternative approaches could be considered before developing or supporting citizen science [111]. However, it should be remembered that there are a myriad of citizen science approaches [75], so simply because one approach does not meet the requirements, other approaches may be more suitable [112]. Additionally, many citizen science projects have already been developed, so be aware that data from existing projects can be reused for additional purposes, thereby avoiding the excessive profileration of many different projects, which can confuse the citizen scientists. Communication and collaboration between project organisers should also help to reduce confusion for potential participants.
When considering doing good citizen science, it is important to consider the diversity of citizen science approaches (Box 1) and their pros and cons. Broadly speaking, contributory citizen science can range from unstructured to systematic, structured approaches [113], but with much variation in between. Unstructured citizen science, in which people take part when and where they choose, leads to uncontrolled spatial variation that needs to be accounted for statistically [102]. Projects should be designed with the analysis in mind to avoid data collection where biases cannot feasibly be accounted for. However, for these, there is the mass participation potential to have many ‘eyes on the ground’ which is ideal for early detection. In contrast, structured monitoring supports standardised data collection which is much closer to typical scientifically designed monitoring, but this requires a high degree of commitment from organisers and volunteers, and long-term commitment from funders (e.g. [74]). Semistructured approaches provide a valuable combination whereby participants take part when and where they choose, but do so in a relatively standardised way, e.g. following a simple protocol [114]. The Backyard Bark Beetles project in the USA (www.backyardbeetles.org) and Bearded Beetle Biodiversity in South Africa (https://citsci.co.za/beetles/) asked people to sample ambrosia beetles using standardised traps made from 2 L drinks bottles. One exciting opportunity is the way in which citizen science can be combined with professional monitoring to create an overall monitoring programme. This means that we can gain the benefits from citizen science (e.g. data collected at greater extents) while reducing the risk of relying solely on citizen science for monitoring and surveillance. This risk arises because volunteers are not obligated to take part in any project, and so could be affected by major societal issues such as the COVID-19 pandemic [115]. A blend of professional and citizen science monitoring can be designed to assess and control for spatial biases in citizen science, e.g. citizen science is more likely to take place in areas of high population density, near roads or in nature reserves [102], and so professionals can fill remaining gaps in a structured way. Additionally, new statistical approaches can be used to combine datasets, for example from structured monitoring (by citizens or by professionals) with opportunistic data [116].
Overall, it is good to adhere to the principles of good citizen science when designing citizen science, e.g. the 10 principles developed by the European Citizen Science Association [117], and to follow existing guides for good practice [118]. Understanding the motivation of participants is an important consideration when developing citizen science. People have a wide range of motivations for participating [119], and this will vary according to the subject of the citizen science project, e.g. long-term monitoring of insect population dynamics versus response to a newly arrived forest pest. Citizen science typically involves people who are relatively well-educated and are involved as an intentional pastime [22]. Some people will be motivated by a desire to connect with nature and do something useful, but when considering tree health, people’s sense of threat could be a strong motivator. For some participants, the opportunity to learn and gain new skills is an important motivator so should be considered in citizen science projects [120, 121]. Linking citizen science to local needs and local action could engage a wider range of participants [116], for example, local woodland owners and forest managers, who see the immediate value in collecting and sharing data for their own management practices. Designing citizen science projects with participants involved (so-called co-created projects) should increase their likelihood of having impact; this probably already happens frequently but is poorly documented because scientific outputs tend to focus on the biological results.
Co-design is a valuable approach to tailoring projects to different stakeholders. For example, early detection of invasive species is often intended for the general public, while early detection of outbreaks may be targeted at forest owners or other people who are regularly in the forest. Matching the scientific needs of a project to a specific audience should support the recruitment and retention of volunteers [119, 122]. It also allows for co-design with specific audiences, which is more effective than seeking to impose activities designed solely by scientists, even if this means adjusting the aims and outcomes from a purely ‘scientific’ perspective. This does not mean that citizen science is a poorer version of professional science; citizen science should, of course, be designed to provide sufficient scientific rigour to be scientifically useful. Co-design will also help to shape the activities around the concerns and needs of participants (where relevant), their skills, and help the teams to consider the ethical dimensions of citizen science and tree health at an early stage in projects [106••, 123]. This is important given the sometimes traumatic consequences of control after early detection of forest pests (e.g. [121]).
One aspect of the scientific usefulness of a citizen science dataset is ensuring the accuracy of data points as well as the fit-for-purpose of the whole dataset. There can be a trade off between ease of participation (and hence completeness of the data) and data quality [124], but this can be ameliorated through careful project co-design. Submitted data such as photos can be verified by professional expert taxonomists [36••] or by expert volunteers. Quality assurance of data points can be supported through volunteer training, which can be delivered in person or virtually [125]. It can also be supported through the verification of records by experts, or it can be automated, e.g. using image recognition where photographs have been submitted [126]. Data verification provides an opportunity for feedback to volunteers. Feedback about records and about the overall project is important for retention and their motivation [60, 127,128,129]. In general, regular communication to participants is valuable to boost their engagement [128].
A well-designed dataflow of the citizen science project is important to make citizen science useful, especially where rapid flow of positive records is required [75]. Technology can support good data flow through tools for data collection, such as websites and apps [130], so that, where appropriate, records can be sent to a responsible authority [36••, 66••, 107, 131]. This enables citizen science to meet the needs of organisers [18]. New automated identification technologies can be used to support rapid data verification [132, 133] and could even be used to automatically harvest records from social media sites [134]. Ultimately, data should adhere to the FAIR principles of findability, accessibility, inter-operability and reusability [135].
Novel Technologies, Approaches and How to Implement Citizen Science in Data-Poor Regions
In recent decades, novel technologies for monitoring pests and diseases have developed rapidly [51]. Many of these technologies are now being used by professionals for the detection and monitoring of native forest pest populations and new pests. On the other hand, many of these technologies, such as the use of drones, have been used by the general public for recreational purposes. In order to utilise these new technologies, citizen scientists can be engaged to assist professionals in monitoring forest pests. Technologies, like drones or citizen sensing (i.e. citizens deploying sensors in the environment), can be applied by the citizen scientists themselves [136, 137] (Table 2). Species-specific lures are available for a range of forest pests (e.g. [138]) and could be particularly valuable because they do not require additional taxonomic expertise for verification of the species, and ethical concerns, e.g. of by-catch of non-pest species in generalised lures, are lessened. When deployed according to a protocol, lures can also provide assessment of population size. Furthermore, citizen scientists can crowd-source the collection of physical samples for laboratory analysis, e.g. inoculation studies [82] or DNA analysis. Professionals can optimise sampling design, and in collaboration with citizen scientists (in terms of co-design), pest monitoring by citizen scientists can provide high-quality data. Examples of this, albeit not related to forest health, are the American Chestnut Foundation which collaborates with scientists and citizen scientists for the collection of leaf tissue for DNA extraction to perform a species‐wide genomic analysis of American chestnut [66••], and an international citizen science project called ‘Pieris Project’ investigated the global invasion history of the agricultural pest butterfly (Pieris rapae) by collecting samples for DNA analysis from 32 countries worldwide [139].
In many areas of environmental science, there is global variation in data available across the world, including from citizen science [79], and great variation in scientific and administrative infrastructures to support research and monitoring. This is also true for research and monitoring of forest pests and diseases. In this review, we have discussed the potential for citizen science to support monitoring and research for forest pests and diseases, so this raises the question: could citizen science be used in places that are currently data poor? From the examples of locally based forest monitoring [140] and arguments about citizen science and vector-borne disease control [141], we conclude that the answer is ‘yes’, citizen science does have a potentially important role. Ashephet et al. [141] state that the benefits of citizen science in data-poor regions are to boost data collection, tap into local knowledge and build partnerships. Citizen science could be particularly impactful where trees and forests directly link to people’s livelihoods and for sustainable development [142, 143], such as in community forests. The Plantwise programme is an interesting approach in which professionals collect data on crop pests by providing an advisory service to people in low- and middle-income countries and thereby collect data on pest impact and spread [144]. New citizen science opens the opportunity for data to be collected in data-poor regions, as demonstrated through citizen science of new data on zoonotic disease vectors in Uganda via participants who were trained and supported by professionals [145]. Here, expertise in citizen science from elsewhere in the world can be brought in, but Ashephet et al. argue that this expertise (often from the Global North) cannot be exported to the Global South, but it must be translated to local situations [141], via co-design to ensure acceptability for local stakeholders [106••, 142]. Indeed, when done well, this can be an effective and sustainable form of monitoring, as demonstrated by the example of ‘community-based monitoring’ for the past 2 decades [146]. The opportunities and recommendations for citizen science as discussed in this review could provide inspiration for designing successful, locally relevant citizen science in data-poor regions. With sufficient investment, this could transform the global monitoring of forest pests.
Conclusions
In a changing world, pest monitoring is becoming very important due to the increasing numbers of new and emerging pests in forests. To increase the early detection of outbreaks and new pests, there should be many eyes in the field. Today, surveys are mostly done by forest health experts, but to increase the potential for early detection, citizen scientists are a welcome addition to monitoring and surveillance of forest pest insects. In the fields of forest protection, the main opportunities for citizen scientists are early warning, early detection of new pests and describing the impact of outbreaks. Additionally, we show that citizen scientists can help with scientific research, which is in many cases underused. Although there is a great potential for citizen science in pest monitoring, every field has its own limitations, opportunities and recommendations that need to be addressed. Therefore, tailored citizen science projects are needed to facilitate successful engagement by citizen scientists. At the moment, citizen scientists are most active in countries that have a strong culture of both citizen science and forest pest monitoring by professional forest health experts. In the future, we see great potential for citizen science in data-poor countries, where the forest health sector is less developed. In this sense, citizen scientists can help to understand and detect outbreaks of new pests faster and avoid problems in the future.
References
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
Blackburn TM, Essl F, Evans T, Hulme PE, Jeschke JM, Kühn I, Kumschick S, Marková Z, Mrugała A, Nentwig W, Pergl J, Pyšek P, Rabitsch W, Ricciardi A, Richardson DM, Sendek A, Vilà M, Wilson JRU, Winter M, Genovesi P, Bacher S. A unified classification of alien species based on the magnitude of their environmental impacts. PLOS Biol. 2014;12:e1001850. https://doi.org/10.1371/journal.pbio.1001850.
Hulme M. Attributing weather extremes to ‘climate change’: a review. Prog Phys Geogr: Earth Environ. 2014;38:499–511. https://doi.org/10.1177/0309133314538644.
Schindler DE, Armstrong JB, Reed TE. The portfolio concept in ecology and evolution. Front Ecol Environ. 2015;13:257–63. https://doi.org/10.1890/140275.
Simberloff D, Martin J-L, Genovesi P, Maris V, Wardle DA, Aronson J, Courchamp F, Galil B, García-Berthou E, Pascal M, Pyšek P, Sousa R, Tabacchi E, Vilà M. Impacts of biological invasions: what’s what and the way forward. Trends Ecol Evol. 2013;28:58–66. https://doi.org/10.1016/j.tree.2012.07.013.
Seidl R, Thom D, Kautz M, Martin-Benito D, Peltoniemi M, Vacchiano G, Wild J, Ascoli D, Petr M, Honkaniemi J, Lexer MJ, Trotsiuk V, Mairota P, Svoboda M, Fabrika M, Nagel TA, Reyer CPO. Forest disturbances under climate change. Nat Clim Chang. 2017;7:395. https://doi.org/10.1038/nclimate3303.
Seebens H, Blackburn TM, Dyer EE, Genovesi P, Hulme PE, Jeschke JM, Pagad S, Pyšek P, Winter M, Arianoutsou M, Bacher S, Blasius B, Brundu G, Capinha C, Celesti-Grapow L, Dawson W, Dullinger S, Fuentes N, Jäger H, Kartesz J, Kenis M, Kreft H, Kühn I, Lenzner B, Liebhold A, Mosena A, Moser D, Nishino M, Pearman D, Pergl J, Rabitsch W, Rojas-Sandoval J, Roques A, Rorke S, Rossinelli S, Roy HE, Scalera R, Schindler S, Štajerová K, Tokarska-Guzik B, van Kleunen M, Walker K, Weigelt P, Yamanaka T, Essl F. No saturation in the accumulation of alien species worldwide. Nat Commun. 2017;8:14435. https://doi.org/10.1038/ncomms14435.
MacDicken K, Jonsson Ö, Piña L, Maulo S, Contessa V, Adikari Y, et al. Global forest resources assessment 2015: how are the world’s forests changing? 2nd ed. Rome: FAO; 2016.
Vega F, Hofstetter R. Bark beetles, biology and ecology of native and invasive species. New York: Academic Press; 2015.
Trumbore S, Brando P, Hartmann H. Forest health and global change. Science. 2015;349:814–8. https://doi.org/10.1126/science.aac6759.
Castello JD, Teale SA. Forest health, an integrated perspective. New York: Cambridge University Press; 2011.
Millar CI, Stephenson NL. Temperate forest health in an era of emerging megadisturbance. Science. 2015;349:823–6. https://doi.org/10.1126/science.aaa9933.
Ramsfield TD, Bentz BJ, Faccoli M, Jactel H, Brockerhoff EG. Forest health in a changing world: effects of globalization and climate change on forest insect and pathogen impacts. Forestry: Int J For Res. 2016;89:245–52. https://doi.org/10.1093/forestry/cpw018.
Hlásny T, König L, Krokene P, Lindner M, Montagné-Huck C, Müller J, Qin H, Raffa KF, Schelhaas M-J, Svoboda M, Viiri H, Seidl R. Bark beetle outbreaks in Europe: state of knowledge and ways forward for management. Curr For Rep. 2021;7:138–65. https://doi.org/10.1007/s40725-021-00142-x.
Herms DA, McCullough DG. Emerald ash borer invasion of North America: history, biology, ecology, impacts, and management. Annu Rev Entomol. 2014;59:13–30. https://doi.org/10.1146/annurev-ento-011613-162051.
Carnegie AJ, Cant RG, Eldridge RH. Forest health surveillance in New South Wales, Australia. Aust For. 2008;71:164–76. https://doi.org/10.1080/00049158.2008.10675031.
Pautasso M. Scientometrics of forest health and tree diseases: an overview. Forests. 2016;7:17.
Roy HE, Pocock MJ, Preston CD, Roy DB, Savage J, Tweddle JC, et al. Understanding citizen science & environmental monitoring. Final report on behalf of UK-EOF. NERC Centre for Ecology & Hydrology and Natural History Museum. 2012:10–1. https://www.ukeof.org.uk/documents/guide-to-citizen-science.
Gupta N, Slawson DD, Moffat AJ. Using citizen science for early detection of tree pests and diseases: perceptions of professional and public participants. Biol Invasions. 2022;24:123–38. https://doi.org/10.1007/s10530-021-02631-3.
Lindenmayer DB, Likens GE. The science and application of ecological monitoring. Biol Conserv. 2010;143:1317–28. https://doi.org/10.1016/j.biocon.2010.02.013.
Parrish JK, Burgess H, Weltzin JF, Fortson L, Wiggins A, Simmons B. Exposing the science in citizen science: fitness to purpose and intentional design. Integr Comp Biol. 2018;58:150–60. https://doi.org/10.1093/icb/icy032.
Pocock MJO, Roy HE, Preston CD, Roy DB. The Biological Records Centre: a pioneer of citizen science. Biol J Linn Soc. 2015;115:475–93. https://doi.org/10.1111/bij.12548.
Pateman R, Dyke A, West S. The diversity of participants in environmental citizen science. Citiz Sci: Theory Pract. 2021;6:9.
Mac Domhnaill C, Lyons S, Nolan A. The citizens in citizen science: demographic, socioeconomic, and health characteristics of biodiversity recorders in Ireland. Citiz Sci: Theory Pract. 2021;5:16.
Petter F, Orlinski A, Suffert M, Roy AS, Ward M. EPPO perspective on Agrilus planipennis (Emerald Ash Borer) and Agrilus anxius (Bronze Birch Borer). Forestry: Int J For Res. 2019;93:220–4. https://doi.org/10.1093/forestry/cpz045.
Rousselet J, Imbert C-E, Dekri A, Garcia J, Goussard F, Vincent B, Denux O, Robinet C, Dorkeld F, Roques A, Rossi J-P. Assessing Species distribution using Google Street view: a pilot study with the pine processionary moth. PLOS ONE. 2013;8:e74918. https://doi.org/10.1371/journal.pone.0074918.
Hester SM, Cacho OJ. The contribution of passive surveillance to invasive species management. Biol Invasions. 2017;19:737–48. https://doi.org/10.1007/s10530-016-1362-4.
• Vetek G, Melifronidou-Pantelidou A, Koukkoularidou D, Martinou A. Initiation of a monitoring programme for early detection of Halyomorpha halys in Cyprus by using pheromone-baited traps and involving citizen science. Manag Biolog Invasions. 2021;12: 331–343. This paper is a nice example of a study focused on the early detection of a highly polyphagous agricultural and nuisance pest (Halyomorpha halys) through a citizen science project.
Meentemeyer RK, Dorning MA, Vogler JB, Schmidt D, Garbelotto M. Citizen science helps predict risk of emerging infectious disease. Front Ecol Environ. 2015;13:189–94. https://doi.org/10.1890/140299.
• Carleton R, Owens E, Blaquière H, Bourassa S, Bowden J, Candau J-N, et al. Tracking insect outbreaks: a case study of community-assisted moth monitoring using sex pheromone traps. 2020. https://doi.org/10.1139/facets-2019-0029. This paper presents a citizen science program to help monitor spruce budworm using pheromone traps that can easily be adapted to monitor any of the numerous organisms for which there is an established trapping method.
Chapman A, Marbus C, Paap T, Burgess T, Hardy G. Citizen science: Community monitoring of Marri canker disease. Australian Network for Plant Conservation Inc; 2015.
Koenig WD, Liebhold AM, Bonter DN, Hochachka WM, Dickinson JL. Effects of the emerald ash borer invasion on four species of birds. Biol Invasions. 2013;15:2095–103. https://doi.org/10.1007/s10530-013-0435-x.
Hulbert JM. Phytophthora diversity in the Cape Floristic Region. 2020; Doctoral thesis.
Pocock MJO, Evans DM. The success of the horse-chestnut leaf-miner, Cameraria ohridella, in the UK revealed with hypothesis-led citizen science. PLOS ONE. 2014;9:e86226. https://doi.org/10.1371/journal.pone.0086226.
•• Castagneyrol B, Valdes-Correcher E, Bourdin A, Barbaro L, Bouriaud O, Branco M, et al. Can school children support ecological research? lessons from the oak bodyguard citizen science project. Citiz Sci: Theory Pract. 2020;5:1–1. https://doi.org/10.5334/cstp.267. This paper evaluates the accuracy of citizen science data by comparing attack rate on fake plasticine caterpillars and insect herbivory estimates by schoolchildren and trained and untrained professional scientists.
•• Valdés-Correcher E, Moreira X, Augusto L, Barbaro L, Bouget C, Bouriaud O, et al. Search for top-down and bottom-up drivers of latitudinal trends in insect herbivory in oak trees in Europe. Glob Ecol Biogeogr. 2021;30: 651–665. https://doi.org/10.1111/geb.13244. This paper investigated the effect of climate on the relationships between plants, herbivores and their predators in Quercus robur through a citizen science project that included the participation of both school and scientific partners.
•• Crow P, Perez-Sierra A, Kavčič A, Lewthwaite K, Kolšek M, Ogris N, et al. Using citizen science to monitor the spread of tree pests and diseases: outcomes of two projects in Slovenia and the UK. Man Biol Invasions. 2020;11:703–719. This paper introduces two similar citizen science projects from different European countries and shows the similarities and differences between them as well as the successful ways in which they have become part of their national approaches to invasive alien species management.
Meeus S, Silva-Rocha I, Adriaens T, Brown P, Chartosia N, Claramunt-López B, et al. BioBlitz is more than a bit of fun. BioScience. https://doi.org/10.1093/biosci/biac100. https://doi.org/10.3897/biss.5.74361.
Eschen R, De Groot M, Glavendekić M, Lacković N, Matosević D, Morales-Rodriguez C, Hanlon RO, Oskay F, Papazova I, Prospero S, Franić I. Spotting the pests of tomorrow—sampling designs for detection of species associations with woody plants. J Biogeogr. 2019;46:2159–73. https://doi.org/10.1111/jbi.13670.
•• de Groot M, O’Hanlon R, Bullas-Appleton E, Csóka G, Csiszár Á, Faccoli M, et al. Challenges and solutions in early detection, rapid response and communication about potential invasive alien species in forests. Manag Biol Invasions. 2020;11:637–660. This paper is an overview of the challenges encountered when developing an early detection and rapid response system for invasive alien species and identifies the similarities in the challenges of early detection, rapid response and communication of these species.
EPPO. Anoplophora glabripennis. EPPO datasheets on pests recommended for regulation. 2022. https://gd.eppo.int. Accessed 15 Jan 2022.
EPPO. Anoplophora chinensis. EPPO datasheets on pests recommended for regulation. 2022. https://gd.eppo.int. Accessed 15 Jan 2022.
Pavesi M. Popillia japonica specie aliena invasiva segnalata in Lombardia. L’Informatore Agrario. 2014;32:53–5.
Baranchikov Y, Mozolevskaya E, Yurchenko G, Kenis M. Occurrence of the emerald ash borer, Agrilus planipennis in Russia and its potential impact on European forestry. EPPO Bull. 2008;38:233–8. https://doi.org/10.1111/j.1365-2338.2008.01210.x.
Tomlinson I, Potter C, Bayliss H. Managing tree pests and diseases in urban settings: the case of Oak Processionary Moth in London, 2006–2012. Urban For Urban Green. 2015;14:286–92. https://doi.org/10.1016/j.ufug.2015.02.009.
Brown N, van den Bosch F, Parnell S, Denman S. Integrating regulatory surveys and citizen science to map outbreaks of forest diseases: acute oak decline in England and Wales. Proc R Soc B: Biol Sci. 2017;284:20170547. https://doi.org/10.1098/rspb.2017.0547.
Andow DA, Borgida E, Hurley TM, Williams AL. Recruitment and retention of volunteers in a citizen science network to detect invasive species on private lands. Environ Manag. 2016;58:606–18. https://doi.org/10.1007/s00267-016-0746-7.
•• Brown N, Pérez-Sierra A, Crow P, Parnell S. The role of passive surveillance and citizen science in plant health. CABI Agric Biosci. 2020;1:17 https://doi.org/10.1186/s43170-020-00016-5. This review describes various forms of passive surveillance and focuses on how the challenges of working with passive surveillance data can be mitigated.
Efsa, Donohoe T, Garnett K, Oude Lansink A, Afonso A, Noteborn H. Emerging risks identification on food and feed–EFSA. EFSA J. 2018;16:5359.
Petter F, Suffert M, McMullen M, Griessinger D, Roy A-S. Seed-borne pests and phytosanitary issues: the role of EPPO. In: Gullino ML, Munkvold G, editors. Global Perspectives on the Health of Seeds and Plant Propagation Material. Dordrecht: Springer, Netherlands; 2014. p. 29–46.
Casula P. Monitoring and management of Cerambyx cerdo in the Mediterranean region – a review and the potential role of citizen science. Nature Conservation. 2017;19:97–110.
Poland TM, Rassati D. Improved biosecurity surveillance of non-native forest insects: a review of current methods. J Pest Sci. 2019;92:37–49. https://doi.org/10.1007/s10340-018-1004-y.
Thomas M, Gunawardene N, Horton K, Williams A, O'Connor S, McKirdy S, Merwe J. Many eyes on the ground: citizen science is an effective early detection tool for biosecurity. Biol Invasions. 2017;19. https://doi.org/10.1007/s10530-017-1481-6.
Kline N, Navarro S, LeBoldus J. Using citizen science and outreach education to reduce the risk of Phytophthora ramorum spread in Oregon forests. In: Frankel SJA, Janice M, editors. Proceedings of the seventh sudden oak death science and management symposium: healthy plants in a world with Phytophthora. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station; 2020. pp.
Barker EJ, Craig A, Winmill A, Meating J, Karandiuk C. Volunteering for forest health: a public-private partnership in Oakville, Ontario, Canada. Arboricult Urban For. 2018;44:283–90.
•• Carnegie AJ, Nahrung HF. Post-border forest biosecurity in Australia: response to recent exotic detections, current surveillance and ongoing needs. Forests. 2019;10:336. This review includes the analysis of data on detection and response by government and industry to exotic forest pest incursions over the last 2 decades, the review of the success of eradication programs and it also makes recommendations.
Rabaglia R, Duerr D, Acciavatti R, Ragenovich I. Early detection and rapid response for non-native bark and ambrosia beetles: summary of the 2001–2005 pilot project. USDA Forest Service, Forest Health Protection; 2008.
Hulbert JM, Agne MC, Burgess TI, Roets F, Wingfield MJ. Urban environments provide opportunities for early detections of Phytophthora invasions. Biol Invasions. 2017;19:3629–44. https://doi.org/10.1007/s10530-017-1585-z.
Seidel M, Lüttke M, Cocquempot C, Potts K, Heeney WJ, Husemann M. Citizen scientists significantly improve our knowledge on the non-native longhorn beetle Chlorophorus annularis (Fabricius, 1787) (Coleoptera, Cerambycidae) in Europe. BioRisk. 2021;16:1–13.
Barham E. The unique role of sentinel trees, botanic gardens and arboreta in safeguarding global plant health. Plant Biosyst - Int J Deal Asp Plant Biol. 2016;150:377–80. https://doi.org/10.1080/11263504.2016.1179231.
Larson L, Cooper C, Futch S, Singh D, Shipley N, Dale K, Lebaron G, Takekawa J. The diverse motivations of citizen scientists: Does conservation emphasis grow as volunteer participation progresses? Biol Conserv. 2020;242:108428. https://doi.org/10.1016/j.biocon.2020.108428.
Tobin PC, Kean JM, Suckling DM, McCullough DG, Herms DA, Stringer LD. Determinants of successful arthropod eradication programs. Biol Invasions. 2014;16:401–14. https://doi.org/10.1007/s10530-013-0529-5.
Valdés-Correcher E, Popova A, Galmán A, Prinzing A, Selikhovkin AV, Howe AG, Mrazova A, Dulaurent A-M, Hampe A, Tack AJM, Bouget C, Lupaștean D, Harvey D, Musolin DL, Lövei GL, Centenaro G, Halder IV, Hagge J, Dobrosavljević J, Pitkänen J-M, Koricheva J, Sam K, Barbaro L, Branco M, Ferrante M, Faticov M, Tahadlová M, Gossner M, Cauchoix M, Bogdziewicz M, Duduman M-L, Kozlov MV, Bjoern MC, Mamaev NA, Fernandez-Conradi P, Thomas RL, Wetherbee R, Green S, Milanović S, Moreira X, Mellerin Y, Kadiri Y, Castagneyrol B. Herbivory on the pedunculate oak along an urbanization gradient in Europe: effects of impervious surface, local tree cover, and insect feeding guild. Ecol Evol. 2022;12:e8709. https://doi.org/10.1002/ece3.8709.
Vétek G, Zach P, Matoševi´c D, Tuba K, Lakatos F, Kulfan J, et al. Invasion by the box tree moth, Cydalima perspectalis (Lepidoptera: Crambidae), in southeastern Europe. In: Invasive dendrophilous organisms: challenges and protection operations. Pushkino: All-Russian Research Institute of Silviculture and Mechanization of Forestry East Palearctic Regional Section International Organization for the Biological Control of Pests and Animals; 2019. pp. 17–28.
de Groot M, Ogris N, van der Meij M, Pocock MJO. Where to search: the use of opportunistic data for the detection of an invasive forest pest. Biol Invasions. 2022. https://doi.org/10.1007/s10530-022-02857-9.
Jordan R, Brooks W, Sorensen A, Ehrenfeld J. Understanding plant invasions: an example of working with citizen scientists to collect environmental data. AIMS Environ Sci. 2014;1:38–44. https://doi.org/10.3934/environsci.2014.1.38.
•• Crocker E, Condon B, Almsaeed A, Jarret B, Nelson CD, Abbott AG, et al. TreeSnap: a citizen science app connecting tree enthusiasts and forest scientists. Plants, People, Planet. 2020;2:47–52. https://doi.org/10.1002/ppp3.41. This paper presents a nice example of a smartphone app developed to connect citizen scientists to restoration tree breeders seeking new tree breeding material and forest pest/pathogen sightings.
Knight KS, Rebbeck J, Cappaert DL, Kula RR, Bauer LS, Bogard DA, et al. Citizen science project leads to emerald ash borer parasitoid discovery. In: Proceedings, Emerald Ash Borer research and technology development meeting, 2009 October 21–22. Pittsburgh PA; 2010. pp. 37–8.
Arnott JC, Osenga EC, Cundiff JL, Katzenberger JW. Engaging stakeholders on forest health: a model for integrating climatic, ecological, and societal indicators at the watershed scale. J For. 2015;113:447–53. https://doi.org/10.5849/jof.14-119.
Hallett R, Hallett T. Citizen science and tree health assessment: how useful are the data? Arboricult Urban For. 2018;44:236–47.
Koenig WD, Liebhold AM. A decade of emerald ash borer effects on regional woodpecker and nuthatch populations. Biol Invasions. 2017;19:2029–37. https://doi.org/10.1007/s10530-017-1411-7.
Ingwell LL, Preisser EL. Using citizen science programs to identify host resistance in pest-invaded forests. Conserv Biol. 2011;25:182–8. https://doi.org/10.1111/j.1523-1739.2010.01567.x.
Cardil A, Vepakomma U, Brotons L. Assessing pine processionary moth defoliation using unmanned aerial systems. Forests. 2017;8:402.
Dennis E, Brereton T, Morgan B, Fox R, Shortall C, Prescott T, et al. Trends and indicators for quantifying moth abundance and occupancy in Scotland. J Insect Conserv. 2019;23. https://doi.org/10.1007/s10841-019-00135-z.
Van Swaay CAM, et al. The EU butterfly indicator for grassland species: 1990–2017: technical report. Butterfly Conservation Europe & ABLE/eBMS. 2019. www.butterfly-monitoring.net.
Pocock MJO, Roy HE, Fox R, Ellis WN, Botham M. Citizen science and invasive alien species: predicting the detection of the oak processionary moth Thaumetopoea processionea by moth recorders. Biol Conserv. 2017;208:146–54. https://doi.org/10.1016/j.biocon.2016.04.010.
Welti EAR, Zajicek P, Frenzel M, Ayasse M, Bornholdt T, Buse J, Classen A, Dziock F, Engelmann RA, Englmeier J, Fellendorf M, Förschler MI, Fricke U, Ganuza C, Hippke M, Hoenselaar G, Kaus-Thiel A, Kerner J, Kilian D, Mandery K, Marten A, Monaghan MT, Morkel C, Müller J, Puffpaff S, Redlich S, Richter R, Rojas-Botero S, Scharnweber T, Scheiffarth G, Yáñez PS, Schumann R, Seibold S, Steffan-Dewenter I, Stoll S, Tobisch C, Twietmeyer S, Uhler J, Vogt J, Weis D, Weisser WW, Wilmking M, Haase P. Temperature drives variation in flying insect biomass across a German malaise trap network. Insect Conserv Divers. 2022;15:168–80. https://doi.org/10.1111/icad.12555.
Karlsson D, Forshage M, Holston K, Ronquist F. The data of the Swedish Malaise Trap Project, a countrywide inventory of Sweden’s insect fauna. Biodivers Data J. 2020;8: e56286.
Parker SS, Pauly GB, Moore J, Fraga NS, Knapp JJ, Principe Z, Brown BV, Randall JM, Cohen BS, Wake TA. Adapting the bioblitz to meet conservation needs. Conserv Biol. 2018;32:1007–19. https://doi.org/10.1111/cobi.13103.
Pocock MJO, Chandler M, Bonney R, Thornhill I, Albin A, August T, Bachman S, Brown PMJ, Cunha DGF, Grez A, Jackson C, Peters M, Rabarijaon NR, Roy HE, Zaviezo T, Danielsen F. Chapter Six - A vision for global biodiversity monitoring with citizen science. In: Bohan DA, Dumbrell AJ, Woodward G, Jackson M, editors. Advances in Ecological Research. Academic Press; 2018. p. 169–223.
Dickinson JL, Zuckerberg B, Bonter DN. Citizen science as an ecological research tool: challenges and benefits. Annu Rev Ecol Evol Syst. 2010;41:149–72. https://doi.org/10.1146/annurev-ecolsys-102209-144636.
Groom Q, Pernat N, Adriaens T, de Groot M, Jelaska SD, Marčiulynienė D, Martinou AF, Skuhrovec J, Tricarico E, Wit EC, Roy HE. Species interactions: next-level citizen science. Ecography. 2021;44:1781–9. https://doi.org/10.1111/ecog.05790.
Garbelotto M, Popenuck T, Hall B, Schweigkofler W, Dovana F, Goldstein de Salazar R, Schmidt D, Sims LL. Citizen science uncovers Phytophthora ramorum as a threat to several rare or endangered California Manzanita Species. Plant Dis. 2020;104:3173–82. https://doi.org/10.1094/pdis-03-20-0619-re.
Gutsch M, Larondelle N, Haase D. Of bugs and men: how forest pests and their management strategies are perceived by visitors of an urban forest. Urban For Urban Green. 2019;41:248–54. https://doi.org/10.1016/j.ufug.2019.03.003.
Fuller L, Marzano M, Peace A, Quine CP, Dandy N. Public acceptance of tree health management: results of a national survey in the UK. Environ Sci Policy. 2016;59:18–25. https://doi.org/10.1016/j.envsci.2016.02.007.
Marzano M, Dandy N, Bayliss HR, Porth E, Potter C. Part of the solution? Stakeholder awareness, information and engagement in tree health issues. Biol Invasions. 2015;17:1961–77. https://doi.org/10.1007/s10530-015-0850-2.
Japelj A, Kus Veenvliet J, Malovrh J, Verlič A, de Groot M. Public preferences for the management of different invasive alien forest taxa. Biol Invasions. 2019;21:3349–82. https://doi.org/10.1007/s10530-019-02052-3.
Jetter K, Paine TD. Consumer preferences and willingness to pay for biological control in the urban landscape. Biol Control. 2004;30:312–22. https://doi.org/10.1016/j.biocontrol.2003.08.004.
Ford-Thompson AES, Snell C, Saunders G, White PCL. Dimensions of local public attitudes towards invasive species management in protected areas. Wildl Res. 2015;42(60–74):15.
Müller M, Job H. Managing natural disturbance in protected areas: tourists’ attitude towards the bark beetle in a German national park. Biol Conserv. 2009;142:375–83. https://doi.org/10.1016/j.biocon.2008.10.037.
Wiggins A, Crowston K. From conservation to crowdsourcing: a typology of citizen science. 44th Hawaii International Conference on System Sciences. 2011.
Mourad KA, Hosseini SH, Avery H. The role of citizen science in sustainable agriculture. Sustainability. 2020;12:10375.
Johnson MF, Hannah C, Acton L, Popovici R, Karanth KK, Weinthal E. Network environmentalism: citizen scientists as agents for environmental advocacy. Glob Environ Chang. 2014;29:235–45. https://doi.org/10.1016/j.gloenvcha.2014.10.006.
Olia A, Tam C, Hendry E, San K. Vancouver’s urban forests: gauging public perceptions and using citizen science to monitor ecological health. Department of Earth, Ocean, and Atmospheric Sciences. 2017. https://doi.org/10.14288/1.0347236.
Flajšman K, de Groot M, Jurc D, Kavčič A, Kus Veenvliet J, Kutnar L, et al. A field guide to invasive alien species in European forests. Ljubljana: Institute Symbiosis, so. e. & the Silva Slovenica Publishing Centre, Slovenian Forestry Institute; 2019.
Morales-Rodríguez C, Anslan S, Auger-Rozenberg M-A, Augustin S, Baranchikov Y, Bellahirech A, Burokienė D, Čepukoit D, Çota E, Davydenko K, Doğmuş Lehtijärvi HT, Drenkhan R, Drenkhan T, Eschen R, Franić I, Glavendekić M, de Groot M, Kacprzyk M, Kenis M, Kirichenko N, Matsiakh I, Musolin DL, Nowakowska JA, O’Hanlon R, Prospero S, Roques A, Santini A, Talgø V, Tedersoo L, Uimari A, Vannini A, Witzell J, Woodward S, Zambounis A, Cleary M. Forewarned is forearmed: harmonized approaches for early detection of potentially invasive pests and pathogens in sentinel plantings. NeoBiota. 2019;47:95–123.
Caley P, Welvaert M, Barry SC. Crowd surveillance: estimating citizen science reporting probabilities for insects of biosecurity concern. J Pest Sci. 2020;93:543–50. https://doi.org/10.1007/s10340-019-01115-7.
Fraisl D, Hager G, Bedessem B, Gold M, Hsing P-Y, Danielsen F, Hitchcock CB, Hulbert JM, Piera J, Spiers H, Thiel M, Haklay M. Citizen science in environmental and ecological sciences. Nat Rev Methods Prim. 2022;2:64. https://doi.org/10.1038/s43586-022-00144-4.
Bonter DN, Cooper CB. Data validation in citizen science: a case study from Project FeederWatch. Front Ecol Environ. 2012;10:305–7. https://doi.org/10.1890/110273.
Wiggins A, Newman G, Stevenson RD, Crowston K. Mechanisms for data quality and validation in citizen science. 2011 IEEE Seventh International Conference on e-Science Workshops. 2011;14–19.
Balázs B, Mooney P, Nováková E, Bastin L, Jokar AJ. Data Quality in Citizen Science. In: Vohland K, Land-Zandstra A, Ceccaroni L, Lemmens R, Perelló J, Ponti M, Samson R, Wagenknecht K, editors. The science of citizen science. Cham: Springer International Publishing; 2021. p. 139–57.
Boakes EH, Gliozzo G, Seymour V, Harvey M, Smith C, Roy DB, Haklay M. Patterns of contribution to citizen science biodiversity projects increase understanding of volunteers’ recording behaviour. Sci Rep. 2016;6:33051. https://doi.org/10.1038/srep33051.
Geldmann J, Heilmann-Clausen J, Holm TE, Levinsky I, Markussen B, Olsen K, Rahbek C, Tøttrup AP. What determines spatial bias in citizen science? Exploring four recording schemes with different proficiency requirements. Divers Distrib. 2016;22:1139–49. https://doi.org/10.1111/ddi.12477.
Mair L, Ruete A. Explaining spatial variation in the recording effort of citizen science data across multiple taxa. PLOS ONE. 2016;11:e0147796. https://doi.org/10.1371/journal.pone.0147796.
Pernat N, Kampen H, Ruland F, Jeschke JM, Werner D. Drivers of spatio-temporal variation in mosquito submissions to the citizen science project ‘Mückenatlas’. Sci Rep. 2021;11:1356. https://doi.org/10.1038/s41598-020-80365-3.
Petersen TK, Speed JDM, Grøtan V, Austrheim G. Species data for understanding biodiversity dynamics: the what, where and when of species occurrence data collection. Ecol Solut Evid. 2021;2:e12048. https://doi.org/10.1002/2688-8319.12048.
•• Pocock MJO, Marzano M, Bullas-Appleton E, Dyke A, de Groot M, Shuttleworth CM, et al. Ethical dilemmas when using citizen science for early detection of invasive tree pests and diseases. Manag Biol Invasions. 2020;11:720–732. This paper identified ethical dilemmas that are pertinent to citizen science for the early detection of invasive tree pests and diseases including the motivations of different stakeholders and participants.
Bell J, Chebli S, Clampitt M, Courtney E, Newstead S, Ramesh N. Obstacles to community participation in reporting pest-related tree damage. Partnership for Action Learning in Sustainability (PALS); 2018.
•• Gardiner MM, Roy HE. The role of community science in entomology. Annu Rev Entomol. 2022;67:437–456. https://doi.org/10.1146/annurev-ento-072121-075258. This review aims to highlight the value of information gathered through citizen science and guide future programs to provide useful data while educating and inspiring participants.
Adriaens T, Van Daele T, Groom Q, Vanderhoeven S, Davis A, Strubbe D, et al. A pipeline to feed headline indicators on the state of invasions and to prioritize emerging alien species for risk assessment. In: The human role in biological invasions: a case of Dr Jekyll and Mr Hyde?: book of abstracts (p. 119). 2020.
Theobald EJ, Ettinger AK, Burgess HK, DeBey LB, Schmidt NR, Froehlich HE, Wagner C, HilleRisLambers J, Tewksbury J, Harsch MA, Parrish JK. Global change and local solutions: tapping the unrealized potential of citizen science for biodiversity research. Biol Conserv. 2015;181:236–44. https://doi.org/10.1016/j.biocon.2014.10.021.
Blaney RJP, Jones GD, Philippe ACV, Pocock MJO. Citizen science and environmental monitoring: towards a methodology for evaluating opportunities, costs and benefits. 2016. https://www.ukeof.org.uk/resources/citizen-science-resources/Costbenefitcitizenscience.pdf
Pocock MJO, Chapman DS, Sheppard LJ, Roy HE. Choosing and using citizen science: a guide to when and how to use citizen science to monitor biodiversity and the environment. Wallingford, Oxfordshire: Centre for Ecology & Hydrology; 2014. http://www.ceh.ac.uk/citizen-science-best-practice-guide.
Pocock MJO, Tweddle JC, Savage J, Robinson LD, Roy HE. The diversity and evolution of ecological and environmental citizen science. PLOS ONE. 2017;12:e0172579. https://doi.org/10.1371/journal.pone.0172579.
Kelling S, Johnston A, Bonn A, Fink D, Ruiz-Gutierrez V, Bonney R, Fernandez M, Hochachka WM, Julliard R, Kraemer R, Guralnick R. Using semistructured surveys to improve citizen science data for monitoring biodiversity. BioScience. 2019;69:170–9. https://doi.org/10.1093/biosci/biz010.
Hochachka WM, Alonso H, Gutiérrez-Expósito C, Miller E, Johnston A. Regional variation in the impacts of the COVID-19 pandemic on the quantity and quality of data collected by the project eBird. Biol Conserv. 2021;254:108974. https://doi.org/10.1016/j.biocon.2021.108974.
Danielsen F, Burgess ND, Balmford A, Donald PF, Funder M, Jones JP, et al.Local participation in natural resource monitoring: a characterization of approaches Conserv Biol: J Soc Conserv Biol. 2009;23:31–42. https://doi.org/10.1111/j.1523-1739.2008.01063.x.
ECSA. 10 Principles of Citizen Science. 2015. https://doi.org/10.17605/OSF.IO/XPR2N.
Tweddle JC, Robinson LD, Pocock MJO, Roy HE. Guide to citizen science: developing, implementing and evaluating citizen science to study biodiversity and the environment in the UK, Natural History Museum and NERC Centre for Ecology and Hydrology for UK-EOF. 2012. https://www.ukeof.org.uk/documents/CitizenScienceReport.pdf.
West S, Dyke A, Pateman R. Variations in the motivations of environmental citizen scientists. Citiz Sci: Theory Pract. 2021;6:14.
Jordan RC, Ballard HL, Phillips TB. Key issues and new approaches for evaluating citizen-science learning outcomes. Front Ecol Environ. 2012;10:307–9. https://doi.org/10.1890/110280.
Turrini T, Dörler D, Richter A, Heigl F, Bonn A. The threefold potential of environmental citizen science - generating knowledge, creating learning opportunities and enabling civic participation. Biol Conserv. 2018;225:176–86. https://doi.org/10.1016/j.biocon.2018.03.024.
Parrish JK, Jones T, Burgess HK, He Y, Fortson L, Cavalier D. Hoping for optimality or designing for inclusion: persistence, learning, and the social network of citizen science. Proc Natl Acad Sci. 2019;116:1894–901. https://doi.org/10.1073/pnas.1807186115.
Porth EF, Dandy N, Marzano M. “My garden is the one with no trees:” residential lived experiences of the 2012 Asian longhorn beetle eradication programme in Kent, England. Hum Ecol. 2015;43:669–79. https://doi.org/10.1007/s10745-015-9788-3.
Lukyanenko R, Wiersma Y, Parsons J. Emerging problems of data quality in citizen science. Conserv Biol. 2016;30:447–9. https://doi.org/10.1111/cobi.12706.
Crall AW, Jordan R, Holfelder K, Newman GJ, Graham J, Waller DM. The impacts of an invasive species citizen science training program on participant attitudes, behavior, and science literacy. Public Underst Sci. 2013;22:745–64. https://doi.org/10.1177/0963662511434894.
Baker E, Drury JP, Judge J, Roy DB, Smith GC, Stephens PA. The verification of ecological citizen science data: current approaches and future possibilities. Citiz Sci: Theory Pract. 2021;6:12.
Hart AG, Adcock D, Barr M, Church S, Clegg T, Copland S, De Meyer K, Dunkley R, Pateman RM, Underhill R, Wyles K, Pocock MJO. Understanding engagement, marketing, and motivation to benefit recruitment and retention in citizen science. Citiz Sci: Theory Pract. 2022;7:5.
MacLeod C, Scott K. Mechanisms for enhancing public engagement with citizen science results. People Nat. 2020;3. https://doi.org/10.1002/pan3.10152.
van der Wal René, Sharma N, Mellish C, Robinson A, Siddharthan A. The role of automated feedback in training and retaining biological recorders for citizen science. Conserv Biol. 2016;30:550–561.
Johnson BA, Mader AD, Dasgupta R, Kumar P. Citizen science and invasive alien species: an analysis of citizen science initiatives using information and communications technology (ICT) to collect invasive alien species observations. Glob Ecol Conserv. 2020;21:e00812. https://doi.org/10.1016/j.gecco.2019.e00812.
Nowak MM, Dziób K, Ludwisiak Ł, Chmiel J. Mobile GIS applications for environmental field surveys: a state of the art. Glob Ecol Conserv. 2020;23:e01089. https://doi.org/10.1016/j.gecco.2020.e01089.
Botella C, Joly A, Bonnet P, Monestiez P, Munoz F. Species distribution modeling based on the automated identification of citizen observations. Appl Plant Sci. 2018;6:e1029. https://doi.org/10.1002/aps3.1029.
Terry JCD, Roy HE, August TA. Thinking like a naturalist: enhancing computer vision of citizen science images by harnessing contextual data. Methods Ecol Evol. 2020;11:303–15. https://doi.org/10.1111/2041-210X.13335.
August TA, Pescott OL, Joly A, Bonnet P. AI naturalists might hold the key to unlocking biodiversity data in social media imagery. Patterns. 2020;1:100116. https://doi.org/10.1016/j.patter.2020.100116.
Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018.https://doi.org/10.1038/sdata.2016.18.
Nitoslawski SA, Galle NJ, Van Den Bosch CK, Steenberg JWN. Smarter ecosystems for smarter cities? A review of trends, technologies, and turning points for smart urban forestry. Sustain Cities Soc. 2019;51:101770. https://doi.org/10.1016/j.scs.2019.101770.
Pucino N, Kennedy DM, Carvalho RC, Allan B, Ierodiaconou D. Citizen science for monitoring seasonal-scale beach erosion and behaviour with aerial drones. Sci Rep. 2021;11:3935. https://doi.org/10.1038/s41598-021-83477-6.
Gonzalez-Audino P, Griffo R, Gatti P, Allegro G, Zerba E. Pheromone detection of the introduced forest pest Megaplatypus mutatus (=Platypus mutatus) (Chapuis) (Platypodinae, Curculionidae) in Italy. Agrofor Syst. 2013;87:109–15. https://doi.org/10.1007/s10457-012-9527-3.
Ryan SF, Lombaert E, Espeset A, Vila R, Talavera G, Dincă V, Doellman MM, Renshaw MA, Eng MW, Hornett EA, Li Y, Pfrender ME, Shoemaker D. Global invasion history of the agricultural pest butterfly Pieris rapae revealed with genomics and citizen science. Proc Natl Acad Sci U S A. 2019;116:20015–24. https://doi.org/10.1073/pnas.1907492116.
Danielsen F, Skutsch M, Burgess ND, Jensen PM, Andrianandrasana H, Karky B, Lewis R, Lovett JC, Massao J, Ngaga Y, Phartiyal P, Poulsen MK, Singh SP, Solis S, Sørensen M, Tewari A, Young R, Zahabu E. At the heart of REDD+: a role for local people in monitoring forests? Conserv Let. 2011;4:158–67. https://doi.org/10.1111/j.1755-263X.2010.00159.x.
Ashepet MG, Jacobs L, Van Oudheusden M, Huyse T. Wicked solution for wicked problems: citizen science for vector-borne disease control in Africa. Trends Parasitol. 2021;37:93–6. https://doi.org/10.1016/j.pt.2020.10.004.
Pocock MJO, Roy HE, August T, Kuria A, Barasa F, Bett J, Githiru M, Kairo J, Kimani J, Kinuthia W, Kissui B, Madindou I, Mbogo K, Mirembe J, Mugo P, Muniale FM, Njoroge P, Njuguna EG, Olendo MI, Opige M, Otieno TO, Ng’weno CC, Pallangyo E, Thenya T, Wanjiru A, Trevelyan R. Developing the global potential of citizen science: assessing opportunities that benefit people, society and the environment in East Africa. J Appl Ecol. 2019;56:274–81. https://doi.org/10.1111/1365-2664.13279.
Fritz S, See L, Carlson T, Haklay M, Oliver JL, Fraisl D, Mondardini R, Brocklehurst M, Shanley LA, Schade S, Wehn U, Abrate T, Anstee J, Arnold S, Billot M, Campbell J, Espey J, Gold M, Hager G, He S, Hepburn L, Hsu A, Long D, Masó J, McCallum I, Muniafu M, Moorthy I, Obersteiner M, Parker AJ, Weisspflug M, West S. Citizen science and the United Nations sustainable development goals. Nat Sustain. 2019;2:922–30. https://doi.org/10.1038/s41893-019-0390-3.
Powell A. CABI’s innovative use of technology, data, and knowledge transfer to reduce crop losses in the developing world. Food Energy Secur. 2017;6:94–7. https://doi.org/10.1002/fes3.113.
Brees J, Huyse T, Tumusiime J, Kagoro-Rugunda G, Namirembe D, Mugabi F, Nyakato V, Anyolitho MK, Tolo CU, Jacobs L. The potential of citizen-driven monitoring of freshwater snails in schistosomiasis research. Citiz Sci: Theory Pract. 2021;6:18.
Danielsen F, Enghoff M, Poulsen MK, Funder M, Jensen PM, Burgess ND. The concept, practice, application, and results of locally based monitoring of the environment. BioScience. 2021;71:484–502.https://doi.org/10.1093/biosci/biab021.
Acknowledgements
EVC was supported by the BNP Paribas Foundation through its Climate and Biodiversity Initiative for the Tree bodyguards citizen science project.
MdG was supported by the core research group Forest biology, ecology and technology (P4-0107) of the Slovenian Research Agency and the Administration for Food Safety, Veterinary Sector and Plant Protection at the Ministry of Agriculture, Forestry and Food of the republic of Slovenia.
MJOP was supported by the Natural Environment Research Council Award No. NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.
JB was supported by the Own Capital of ILVO and several projects funded by FPS Public Health Belgium.
We acknowledge support from the COST action Alien CSI ‘Increasing understanding of alien species through citizen science’ (COST Action CA17122).
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de Groot, M., Pocock, M.J.O., Bonte, J. et al. Citizen Science and Monitoring Forest Pests: a Beneficial Alliance?. Curr Forestry Rep 9, 15–32 (2023). https://doi.org/10.1007/s40725-022-00176-9
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DOI: https://doi.org/10.1007/s40725-022-00176-9